More Ways to Drive Qualified Leads in Autopilot: Introducing the Change Score Action
Recently Autopilot rolled out the new “Change Score” action. For the first time, you can easily increase or decrease any field by a specified amount, in order to track engagement by counting email clicks, Headsup responses, in-product actions, and more.
Doesn’t this contradict our previous commentary that traditional lead scoring is broken? Well, no – the new Change Score feature adds value to Autopilot users who want the flexibility to incorporate activity or engagement counts into their lead qualification framework. By itself, the Change Score action is not a silver bullet solution to the problem of how to drive a steady stream of qualified leads. Doing that can be achieved through a cohesive strategy involving at least six methods, as discussed previously.
But don’t get me wrong, this new shape offers unmatched flexibility to count actions, score leads, and fine-tune your qualification framework. In this post, we’ll share how people are using Autopilot to qualify and assign leads that leave their sales teams screaming for more.
Step 1: Determine your key targeting criteria
Drill into the core segments or target personas who you are selling to and analyze past wins and losses. Did winners have specific job titles, use cases, or needs that characterize them as “market center” for your product? Did they pick a competitor that you stack well against but aren’t well positioned against? Did they lack technical expertise, or fail to grasp your business value? Was there no compelling reason to evaluate and buy now vs. 6 months from now?
Identify key demographic (describing the people) and behavioral (describing the actions) data that you can capture or compile, to better define your target audience, and develop messaging and engagement journeys to counter the above challenges. Examples include:
Autopilot enables you to gather demographic data from many sources, including tracked forms, Proactive Headsup (onsite lead capture), your CRM or uploaded lists. Behavioral data is gathered using the Autopilot tracking code, or syncing data in Autopilot from your product, Segment, billing system, or via our API.
Step 2: Define a “Marketing Qualified Lead” (MQL)
Next, define how you will route and prioritize inbound and nurtured leads (outbound lead generation is a different conversation). The lead to customer funnel typically breaks down as:
Raw leads are any names ingested into your marketing system, including form completions, list uploads, web signups, proactive headsups. You may assign all of these to your sales team or CRM (1:1 lead syncing), or only those who meet your targeting criteria. These are Marketing Qualified Leads (MQLs).
There are two types of marketing qualified leads (MQLs):
- Those which are immediately assigned to sales or sales development (sometimes called Primary MQLs), including Contact Sales, demo or trial requests. These are the leads sales wants.
- Those who need to be qualified (sometimes called Secondary MQLs) based on the targeting factors discussed, above using lead scoring or segments.
As a general rule of thumb, 15% – 20% of MQLs should convert into a win. Any lower and you’re wasting sales’ time; higher and you’re being too conservative and can afford to pass more leads. The trick to achieving this is to qualify leads upfront, assign MQLs to sales, and route unqualified leads to self-service or nurturing, until they show buying signs and can be re-assigned to sales.
Step 3: Trigger MQL creation using Smart Segments and Lead Scores
Once you have determined the demographic and behavioral signals that define a qualified lead at your company, it’s time to set it up in Autopilot. This can be accomplished in several ways. Use Smart Segments, Lead Score (shape), or a combination of the two to define a raw lead as a (Secondary) MQL, as show in the examples below:
- Smart Segment based on contacts who have signed up for a trial AND are in a >500 employee company AND have clicked 20 emails
- Lead Score (value) that is 50+ points where a trial signup is worth 20 points, a >500 employee company is worth 10 points, and email clicks are worth 1 each
Lead scoring gained popularity as a way to deal with weighing all these different signals based on their perceived value, but the reality of the matter is that there are thousands of signals you want to take into account. (That’s why there are predictive solutions, but more on that to come.)
Keep it simple. Focus on the signals that truly matter.
Step 4: Use a qualification journey to assign MQLs (capture + route)
The final step is to determine how to follow up with leads once they are marketing qualified, which can vary based on your lead volume and sales model:
- Option 1: Assign every lead to sales (or at least every primary MQL).
If you work with enterprise companies that require a bit more personal hand holding or simply have a low lead volume, it may make sense to send each lead directly to sales. And those primary MQLs we defined earlier? If they requested a response, make sure they’re routed accordingly and followed up with as well.
- Option 2: Use smart segments, field values or both to include or exclude contacts based on demographics or behavior.
If you have a product or solution that branches across multiple groups, you may choose to focus on behavior events more than demographics. Conversely, you may have a very specific target buyer, so if you can identify these ideal candidates, you likely want to start the conversation as soon as possible.
- Option 3: Use smart segments, field values or both to include or exclude contacts based on demographics and behavior.
Remember: keep it simple. Here at Autopilot, we look at our contacts’ Infer predictive fit (demographic score), then layer on forms completed and emails clicked using the new “Change Score” action (behavioral scoring) to identify qualified nurture leads and ensure no qualified lead slips through the cracks.
Use scoring to complement your lead qualification, not determine it
Autopilot’s new “Change Score” action allows you to score leads, gather more customer information, and enrich your lead qualification process. We suggest keeping it simple, and looking for “no brainer” signals of qualification to get results.
If you really want to get sophisticated with lead scoring, then you need to look at far more signals than you likely have (easy) access to, including technology usage, hiring status, funding history, prior buying history, location, area code or email domain performance, website structure, online reviews, spam filtering, etc. The list is practically endless, which is why predictive lead scoring services like Infer exist, but we find them to be invaluable for focusing and aligning the organization around truly qualified leads.
But enough about us – how are you qualifying leads with Autopilot today? How do you envision yourself using the new shape? Let us know in the comments below.